Returns:
            A PromptTemplate with the template assembled from the pieces here.
        """
        tool_strings = "\n".join([f"{tool.name}: {tool.description}" for tool in tools])
        tool_names = ", ".join([tool.name for tool in tools])
        format_instructions = format_instructions.format(tool_names=tool_names)
        template = "\n\n".join([prefix, tool_strings, format_instructions, suffix])
        if input_variables is None:
            input_variables = ["input", "agent_scratchpad"]
        return PromptTemplate(template=template, input_variables=input_variables)
[docs]    @classmethod
    def from_llm_and_tools(
        cls,
        llm: BaseLLM,
        tools: Sequence[BaseTool],
        callback_manager: Optional[BaseCallbackManager] = None,
        prefix: str = PREFIX,
        suffix: str = SUFFIX,
        format_instructions: str = FORMAT_INSTRUCTIONS,
        input_variables: Optional[List[str]] = None,
        **kwargs: Any,
    ) -> Agent:
        """Construct an agent from an LLM and tools."""
        cls._validate_tools(tools)
        prompt = cls.create_prompt(
            tools,
            prefix=prefix,
            suffix=suffix,
            format_instructions=format_instructions,
            input_variables=input_variables,
        )
        llm_chain = LLMChain(
            llm=llm,
            prompt=prompt,
            callback_manager=callback_manager,
        )
        tool_names = [tool.name for tool in tools]
        return cls(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
    @classmethod
    def _validate_tools(cls, tools: Sequence[BaseTool]) -> None:
        for tool in tools: